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What Is a Chatbot?
A chatbot (also known as a chatterbot or virtual assistant) is a computer program that’s designed to emulate human conversation and converse with human users.
Many virtual assistants, such as ChatGPT and Gemini, are AI-driven. They use techniques like natural language processing (NLP) and natural language understanding (NLU) to analyze and respond to user inputs.
A chatbot’s primary meaning is a program that can interact with users. Many virtual assistants or chatbots will use artificial intelligence (AI) and machine learning (ML) to process and respond to user inputs in multiple formats, such as text and voice.
That being said, while some chatbots use AI to process and respond to user inputs, not all do. For example, an FAQ-style chatbot could be given a pre-programmed list of responses to certain questions.
Key Takeaways
- Chatbots are programs designed to mimic human conversation, often powered by AI and using natural language processing to understand and respond to users.
- There are different types of chatbots, such as menu-based, rules-based, AI-powered, voice chatbots, and generative AI chatbots, each serving specific purposes.
- They are commonly used for tasks like customer service, marketing, content creation, and research, making repetitive tasks more efficient.
- While chatbots improve efficiency and reduce costs, they can lack a personal touch and sometimes struggle with accuracy.
- The future of chatbots includes multimodal capabilities, allowing them to handle text, voice, image, and video inputs for more dynamic interactions.
History of Chatbots
Under our chatbot definition, the first chatbot can be traced back to ELIZA, developed in the 1960s by MIT professor Joseph Weizenbaum. Released in 1966, ELIZA emulated a Rogerian psychotherapist and used natural language processing to pair user inputs with a list of scripted responses. These capabilities made it able to mimic human conversation.
Another key milestone in the development of virtual assistant technology was the creation of a chatbot known as Jabberwacky by British computer scientist Rollo Carpenter in 1989. This chatbot was designed to simulate human interaction and could interact with users via text.
While ELIZA and Jabberwacky were ahead of their time, it would take until 2009 and the release of the Chinese app, WeChat for chatbots capabilities to really start to evolve. WeChat’s chatbot has become a staple tool for creating chatbots.
However, the boundaries of chatbot AI would really start to be pushed just a year later when Apple launched Siri, a virtual assistant that was made via the iPhone 4S in October 2011. Users could interact with Siri via voice and ask questions on a variety of topics.
Around this time, Google and Microsoft released similar voice-driven chatbots, Google Assistant and Cortana in 2012 and 2014, but the most significant was undoubtedly the launch of Amazon Alexa in 2014 alongside its Echo line of devices.
Finally, in 2022 OpenAI announced the launch of >ChatGPT, its flagship generative AI (genAI) chatbot, which kickstarted a large language model (LLM) arms race among key companies like Microsoft and Google.
In 2023, a number of notable LLMs launched, including:
These releases were followed up by a number of updates in 2024, with OpenAI launching its multimodal GPT-4o model, an advanced reasoning model known as o1, and announcing its successor model o3. Other big LLM releases in 2024 included Claude 3.5 Sonnet, Grok 2, and Llama 3.
How a Chatbot Works
Typically a user enters an input into a user interface via text or voice. The chatbot then uses natural language processing to analyze the request, scanning for particular keywords and phrases and then taking one of the following actions:
- Search a database of pre-programmed responses and provide a relevant answer.
- Use natural language generation to create a response based on its training data.
Each of these two actions enables the chatbot to generate an output that responds to the user’s input with relevant information. The user can then ask follow-up questions if they require more assistance.
Types of Chatbots
Chatbot Use Cases
Today, chatbots can be used in a wide range of scenarios.
Some of the most common use cases are as follows:
Users can use a chatbot connected to the Internet, such as Perplexity AI or Gemini, to query publicly scraped content to assist when researching a given topic.
Generative AI-driven chatbots such as ChatGPT or Claude 3 can be used to generate content on demand.
Menu-based and rule-based chatbots can be used to automate customer service tasks, from asking questions about item specifications, delivery policies, and returns policies, to making a complaint, leaving a review, or requesting access to a human customer support agent.
Chatbot Pros & Cons
Using chatbots comes with a number of distinct advantages and disadvantages.
Some of the main pros and cons are outlined below:
Pros
- Enhance customer service
- Increase sales
- Reduce costs
Cons
- Lack of a personal touch
- Accuracy
- Upfront costs
- Increase complexity
The Future of Chatbots
As of 2025, the future of chatbots looks bright. Throughout 2023 we saw the launch of chatbots, including the GPT-4 version of ChatGPT, Claude, Bing Chat, Gemini, Grok, and Llama 2.
While these chatbots initially started as text-to-text tools, from 2023-2024, we began to see AI vendors like OpenAI, Anthropic, Google, and x.AI incorporating multimodality. We now see a new generation of LLMs capable of handling a mix of text, voice, image, and video inputs.
In the future, we’re also likely to see a new generation of humanoid robots like the Tesla Optimus and Figure 02 using generative AI as a key enabler to better interact with humans in the workplace.
The Bottom Line
Chatbots have gradually entered enterprise workflows as a staple tool. While they aren’t suitable for every scenario, they do provide an option to automate basic repeatable tasks and will, in the future, be able to respond to user requests much more reliably.
